Embarking on a journey to expand your business, acquire prime real estate, or boost working capital? A commercial loan often emerges as the beacon of hope in such ventures. However, getting approval for a commercial loan is not an easy feat.
The underwriting process is often surrounded by inefficiencies, delays, and subjective decision-making. Lenders grapple with unseen challenges such as unreliable and/or inaccessible data, lengthy document processing, and regulatory adherence, questioning their ability to approve/reject a loan application. In response, AI-enabled commercial loan underwriting has dawned, redefining how lenders or bankers evaluate and approve the loan.
This article delves into the transformative potential of AI in commercial loan underwriting and offers insights into how to leverage this technology to streamline processes, mitigate risks, and unlock new opportunities in lending.
What is Commercial Loan Underwriting?
Commercial underwriting encompasses collecting and analyzing information to make well-informed decisions regarding the approval or rejection of commercial credit or loan applications.
The commercial underwriting process entails a thorough analysis of multiple factors such as the borrower's financial statements, credit history, business plans, collateral, and industry trends.
The primary objective of commercial underwriting is to assess the borrower's capability to repay the loan in adherence to the agreed-upon terms, while also mitigating risk exposure for the lender.
Commercial Loan Underwriting Process
Commercial loan underwriting has a structured process encompassing three categories:
Background Verification
In the general background check, the underwriter must assess- What is the credit history of business and principal owners, including credit scores and any previous defaults? Has the lender engaged with this borrower in prior loan transactions?
- What is the intended use of the funds? Are there valid business reasons for the loan? How will the loan impact the overall business?
- What is the business history, and how it is anticipated to perform in the future? Are there well-prepared and realistic business projections for the future?
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Repayment Ability Assessment
- An imperative consideration is to check the possibility of timely repayment. The underwriter relies on the business's historical performance and future projections to conduct this assessment.
- A primary analytical tool used by lenders is financial ratio analysis. One of the pivotal metrics is the "Coverage Ratio." This compares the anticipated profits or cash flow of the business and the ongoing loan payments required to repay the loan.
- The other ratios include the Debt/Equity Ratio, i.e., the amount of business debt versus business equity. A business with a higher debt-to-equity ratio signifies a less robust financial standing. A business may only withstand temporary setbacks if owners have external financial resources to contribute.
- The ratio of a business's inventory to its sales volume will indicate the turnover rate, reflecting how quickly products are bought and sold. A sluggish inventory turnover could suggest obsolescence or inadequate management practices within the company.
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Security and Other Assets Evaluation
- Lenders must seek adequate assets to use as security against a loan default. They must evaluate business assets produced by the loan itself or other business assets.
- Additionally, security be can extended to personal guarantees from owners or external assets such as real estate, stocks, securities, or other business interests owned by the borrower.
What are the Risks Associated with Commercial Underwriting?
There are several types of risks associated with commercial loan underwriting:
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Default Risk:
This refers to the possibility that the borrower may fail to repay the loan as agreed. In such cases, the lender may take legal measures to recover the outstanding debt. -
Interest Rate Risk:
This is the risk that the interest rate on the loan may rise, leading to increased repayment costs for the borrower. -
Prepayment Risk:
This pertains to the possibility that the borrower may repay the loan before the scheduled maturity date, resulting in the lender receiving fewer interest payments than anticipated. -
Credit Risk:
This denotes the risk associated with the borrower's inability to make timely payments due to financial difficulties. -
Fraud Risk:
This represents the risk that the borrower may misuse the loan funds for unauthorized purposes, such as personal expenses or uncertain investments. -
Collateral Risk:
This refers to the risk that the collateral used to secure the loan, such as a property or vehicle, may not be sufficient to cover the outstanding loan amount in case of borrower default. -
Economic Risk:
This is the risk stemming from adverse economic conditions, such as a recession making it challenging for the borrower to repay a loan.
However, bankers and lenders can mitigate risks using AI. Identifying potential risk exposures automatically during the underwriting process allows them to make more robust and reliable lending decisions, ultimately ensuring greater efficiency, accuracy, and customer satisfaction.
AI-automated Commercial Underwriting
Today, underwriters are faced with an increasing number of variables, submissions, competition, and data of various types. This is why more banks or insurance firms are turning to AI in commercial underwriting.
AI/ML is particularly effective in handling the large volumes of data that underwriters encounter. These technologies are transforming the way underwriters work and providing significant advantages to underwriting processes overall. This results in exceptional customer experience, superior employee experience, compliance and fraud prevention, and improved business decisions.
Traditional Underwriting Vs AI Automated Commercial Underwriting
Traditional underwriting refers to the conventional process of assessing risks and determining applicant eligibility for loans or insurance policies. In this approach, underwriters hugely depend on manual methods and human judgment to evaluate factors such as financial history, creditworthiness, and an applicant's risk profile.
While traditional underwriting has been effective for many years, it can be time-consuming, prone to human error, and less adaptable to changing market conditions. Additionally, using the traditional approach puts bankers and lenders under pressure to expand, cope with pricing pressure, and navigate increased competition.
A growing emphasis on adopting automation for underwriting can be noticed. Automated capabilities are being leveraged to boost underwriters' productivity and decision-making quality, leading to increased operational efficiency and profitability.
The below table illustrates the distinctions between traditional and automated underwriting based on business context:
Aspect | Traditional Underwriting | Automation in Underwriting |
Risk Assessment | Emphasize comprehensive risk coverage and pricing strategies | Focus on prevention, customer experience, and fueling growth |
Data collection | Collect pertinent information through client interactions and paperwork | Automated data integration from data internal and external resources |
Decision-making process | Experience-driven expertise & decision-making | Data and analytics-led decision-making |
Customization | Segmenting risks and pricing based on established rules | Personalized risk profiling and improved underwriting |
5 Benefits of Using Automated AI Commercial Underwriting Software
Here are some benefits of implementing automated commercial underwriting
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Strategic Allocation of Resources
Leveraging AI-automated commercial underwriting software allows lenders to process loan applications swiftly, allowing human underwriters to focus on more intricate use cases. With strategic resource allocation, lenders can manage multiple loan applications, provide personalized services to borrowers, and foster long-term business expansion. -
Proactive Fraud Detection
Implementing the software in underwriting can significantly reduce the occurrence of fraud. Underwriters can deploy predictive analytics to monitor risks associated with loan underwriting and disbursement. Automation in commercial underwriting promptly identifies and flags fraudulent transactions, leading to a proactive and effective fraud prevention system. -
Informed Decision-making
Automated underwriting counts on standard procedures aligning with the principles of lending institutions. This automation empowers lenders to tailor the underwriting and loan disbursal to individual needs, adhering to standardized policies.
As lenders have varied interpretations of underwriting policies, this automation minimizes the discrepancies throughout the process. -
Streamlined Compliance & Auditing
Underwriting norms and regulations undergo periodic changes, potentially impacting the entire underwriting process. Additionally, manual procedures often lead to overlooking these evolving guidelines. Leveraging automated underwriting ensures better compliance by integrating changes across the entire process with a single adjustment in an algorithm.
Similar to regulatory adherence, auditing of underwriting institutions is crucial for effective governance. Automation in commercial underwriting simplifies and streamlines the auditing process, eliminating the necessity of manual examination of large documentation. Furthermore, it reduces the likelihood of errors, and guarantees a detailed auditing approach, thus preventing fraudulent transactions. -
Efficient Paperless Loan Approval
Implementing AI-automated commercial underwriting can reduce the need for extensive paperwork. The reliance on physical documents would be minimized, leading to reduced storage requirements, lower imaging expenses, and diminished costs associated with delivery personnel. The rule-based data system is crucial in eliminating paper and reducing the chances of forgery or misrepresentation of signatures.
Indeed, integrating AI-powered commercial underwriting can greatly expedite the process for bankers and lenders. Recognizing the demand to reduce the time and effort needed for paperwork, we offer an advanced AI-powered underwriting platform. By automating processes, we fortify accuracy and consistency, leading to shorter wait times for loan applicants.
FAQs
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How long does the commercial loan underwriting process take?
The duration of the commercial loan underwriting process can vary significantly, spanning from three to five business days to several months. The exact timeline is influenced by various factors, such as the size and complexity of the business, the underwriter's procedures and workload, and the volume of documents requiring review. -
What are the documents typically required for the commercial loan underwriting process?
Commercial loan underwriting often requires various documents, including financial statements such as balance sheets, and income statements, cash flow statements, business tax returns, personal tax returns, business plans, lease agreements, and information on any existing debts or liabilities. -
What are the steps in the underwriting process?
Here are the steps in the underwriting process for a commercial loan in a very concise format:- Application Submission
- Initial Review
- Financial Analysis
- Credit Analysis
- Collateral Evaluation
- Risk Assessment
- Decision Making
- Conditional Approval
- Final Approval and Closing
- Funding
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What are the five Cs of Commercial Underwriting?
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Character:
This pertains to the borrower's track record of bill payment and financial responsibility. -
Capacity:
This involves assessing whether the borrower has sufficient income to meet their debt obligations. -
Capital:
Also referred to as equity, this reflects the borrower's level of investment in the business. A higher equity contribution generally indicates a lower risk for the lender. -
Collateral:
This serves as an alternative source of repayment if the borrower's cash flow proves inadequate to cover the debt. -
Conditions:
Referred to as loan structure, this encompasses both the terms of the loan (such as interest rate) and any specific conditions imposed to ensure repayment.
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